2,803 research outputs found

    Spike-based VITE control with Dynamic Vision Sensor applied to an Arm Robot.

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    Spike-based motor control is very important in the field of robotics and also for the neuromorphic engineering community to bridge the gap between sensing / processing devices and motor control without losing the spike philosophy that enhances speed response and reduces power consumption. This paper shows an accurate neuro-inspired spike-based system composed of a DVS retina, a visual processing system that detects and tracks objects, and a SVITE motor control, where everything follows the spike-based philosophy. The control system is a spike version of the neuroinspired open loop VITE control algorithm implemented in a couple of FPGA boards: the first one runs the algorithm and the second one drives the motors with spikes. The robotic platform is a low cost arm with four degrees of freedom.Ministerio de Ciencia e Innovación TEC2009-10639-C04-02/01Ministerio de Economía y Competitividad TEC2012-37868-C04-02/0

    Low-Power Tracking Image Sensor Based on Biological Models of Attention

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    This paper presents implementation of a low-power tracking CMOS image sensor based on biological models of attention. The presented imager allows tracking of up to N salient targets in the field of view. Employing "smart" image sensor architecture, where all image processing is implemented on the sensor focal plane, the proposed imager allows reduction of the amount of data transmitted from the sensor array to external processing units and thus provides real time operation. The imager operation and architecture are based on the models taken from biological systems, where data sensed by many millions of receptors should be transmitted and processed in real time. The imager architecture is optimized to achieve low-power dissipation both in acquisition and tracking modes of operation. The tracking concept is presented, the system architecture is shown and the circuits description is discussed

    A Foveated Silicon Retina for Two-Dimensional Tracking

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    A silicon retina chip with a central foveal region for smooth-pursuit tracking and a peripheral region for saccadic target acquisition is presented. The foveal region contains a 9 x 9 dense array of large dynamic range photoreceptors and edge detectors. Two-dimensional direction of foveal motion is computed outside the imaging array. The peripheral region contains a sparse array of 19 x 17 similar, but larger, photoreceptors with in-pixel edge and temporal ON-set detection. The coordinates of moving or flashing targets are computed with two one-dimensional centroid localization circuits located on the outskirts of the peripheral region. The chip is operational for ambient intensities ranging over six orders of magnitude, targets contrast as low as 10%, foveal speed ranging from 1.5 to 10K pixels/s, and peripheral ON-set frequencies from \u3c0.1 to 800 kHz. The chip is implemented in 2-μm N well CMOS process and consumes 15 mW (V dd = 4 V) in normal indoor light (25 μW/cm2). It has been used as a person tracker in a smart surveillance system and a road follower in an autonomous navigation system

    Pixel Detectors

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    Pixel detectors for precise particle tracking in high energy physics have been developed to a level of maturity during the past decade. Three of the LHC detectors will use vertex detectors close to the interaction point based on the hybrid pixel technology which can be considered the state of the art in this field of instrumentation. A development period of almost 10 years has resulted in pixel detector modules which can stand the extreme rate and timing requirements as well as the very harsh radiation environment at the LHC without severe compromises in performance. From these developments a number of different applications have spun off, most notably for biomedical imaging. Beyond hybrid pixels, a number of monolithic or semi-monolithic developments, which do not require complicated hybridization but come as single sensor/IC entities, have appeared and are currently developed to greater maturity. Most advanced in terms of maturity are so called CMOS active pixels and DEPFET pixels. The present state in the construction of the hybrid pixel detectors for the LHC experiments together with some hybrid pixel detector spin-off is reviewed. In addition, new developments in monolithic or semi-monolithic pixel devices are summarized.Comment: 14 pages, 38 drawings/photographs in 21 figure

    Single-chip CMOS tracking image sensor for a complex target

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    Fast neural algorithms for detecting moving targets in highly noisy environments

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    The detection of targets moving in an environment dominated by "noise" is addressed from the perspective of nonlinear dynamics. Sensor data are used to drive a Korteweg-deVries (soliton) equation, inducing a resonance-type phenomenon which indicates the presence of hidden target signals. The algorithm is implemented in terms of a novel neural architecture, which we have named "spectral network", which can easily be implemented in optoelectronic hardware
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